def test_groupby():
shuffle_idx = np.random.permutation(np.arange(100))
index = np.tile(np.arange(10), 10)
data = np.vstack([np.identity(10) for _ in range(10)])
t = SparseFrame(data[shuffle_idx, :], index=index[shuffle_idx])
res = t.groupby_sum().data.todense()
assert np.all(res == (np.identity(10) * 10))
def test_groupby_dense_random_data():
shuffle_idx = np.random.permutation(np.arange(100))
index = np.tile(np.arange(10), 10)
single_tile = np.random.rand(10, 10)
data = np.vstack([single_tile for _ in range(10)])
t = SparseFrame(data[shuffle_idx, :], index=index[shuffle_idx])
res = t.groupby_sum().data.todense()
np.testing.assert_array_almost_equal(res, (single_tile * 10))